Those who attempt to deceive electronic consumers with fraudulent e-mail messages and web sites often embed the logo of a legitimate company in the fraudulent e-mail or web page in an attempt to add credibility. Current fraud detection methods can track Uniform Resource Locators (URLs) that have been determined to point to fraudulent sites, but these methods can be made more accurate and more proactive if the fraudulent use of a legitimate logo used by the perpetrator can be identified. If, for example, an e-mail message contains the logo of an e-commerce or financial institution, and also contains URLs that point to web sites that do not belong to or are not sanctioned by the relevant institution, not only can the e-mail message be classified as fraudulent, but the URLs it contains can be added to a blacklist of URLs known to be used for fraud.
However, it can be extremely difficult to distinguish fraudulent image content from legitimate image content. Known image identification techniques such as hashing or various transform-based methods are easily defeated by slight modifications to the image, such as manipulation of the color levels of individual pixels or embedding the logo in a larger image. Such modifications typically cannot be detected visually by the end user. Thus, logo images can be used fraudulently by making minor modifications which are sufficient enough to spoof traditional image detection methods, but minor enough to go undetected by the naked eye.
What is need are methods, systems and computer readable media for robustly detecting images even when they have been subjected to these and other evasive techniques.